Update app.py

app.py

@@ -8,12 +8,10 @@ from langgraph.graph import StateGraph, MessagesState, START
 from langchain_core.messages import SystemMessage, HumanMessage
 from langchain_community.document_loaders import WikipediaLoader
 from langchain_community.tools import TavilySearchResults, DuckDuckGoSearchRun
-from dotenv import load_dotenv
 import operator
 from typing import Annotated
 from typing_extensions import TypedDict
 
-load_dotenv()
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -44,75 +42,76 @@ class State(TypedDict):
     answer: str
     context: Annotated[list, operator.add]
 
-    def search_tavily(state):
+def search_tavily(state):
     
-        """ Retrieve docs from web search """
-
-        # Search
-        tavily_search = TavilySearchResults(max_results=2)
-        search_docs = tavily_search.invoke(state['question'])
-
-         # Format
-        formatted_search_docs = "\n\n---\n\n".join(
-            [
-                f'<Document href="{doc["url"]}"/>\n{doc["content"]}\n</Document>'
-                for doc in search_docs
-            ]
-        )
+    """ Retrieve docs from web search """
+
+    # Search
+    tavily_search = TavilySearchResults(max_results=2)
+        
+    search_docs = tavily_search.invoke(state['question'])
+
+    # Format
+    formatted_search_docs = "\n\n---\n\n".join(
+        [
+            f'<Document href="{doc["url"]}"/>\n{doc["content"]}\n</Document>'
+            for doc in search_docs
+        ]
+    )
 
-        return {"context": [formatted_search_docs]}
+    return {"context": [formatted_search_docs]}
 
-    def search_wikipedia(state):
+def search_wikipedia(state):
     
-        """ Retrieve docs from wikipedia """
+    """ Retrieve docs from wikipedia """
 
-        # Search
-        search_docs = WikipediaLoader(query=state['question'], 
+    # Search
+    search_docs = WikipediaLoader(query=state['question'], 
                                   load_max_docs=2).load()
 
-         # Format
-        formatted_search_docs = "\n\n---\n\n".join(
-            [
-                f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content}\n</Document>'
-                for doc in search_docs
-            ]
-        )
+    # Format
+    formatted_search_docs = "\n\n---\n\n".join(
+        [
+            f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}"/>\n{doc.page_content}\n</Document>'
+            for doc in search_docs
+        ]
+    )
 
-        return {"context": [formatted_search_docs]}
+    return {"context": [formatted_search_docs]}
 
-    def search_DuckDuckGo(state):
+def search_DuckDuckGo(state):
 
-        """ Retrive answer from DuckDuckGoSearch."""
+    """ Retrive answer from DuckDuckGoSearch."""
 
-        ddg_search = DuckDuckGoSearchRun(max_results=2)
-        search_docs = ddg_search.invoke(state['question'])
+    ddg_search = DuckDuckGoSearchRun(max_results=2)
+    search_docs = ddg_search.invoke(state['question'])
 
-         # Format
-        formatted_search_docs = "\n\n---\n\n".join(
-            [
-                f'<Document href="{doc["url"]}"/>\n{doc["content"]}\n</Document>'
-                for doc in search_docs
-            ]
-        )
+    # Format
+    formatted_search_docs = "\n\n---\n\n".join(
+        [
+            f'<Document href="{doc["url"]}"/>\n{doc["content"]}\n</Document>'
+            for doc in search_docs
+        ]
+    )
 
-        return {"context": [formatted_search_docs]}
+    return {"context": [formatted_search_docs]}
 
-    def generate_answer(state):
+def generate_answer(state):
 
-        """Node to give answer to the question"""
+    """Node to give answer to the question"""
 
-        context = state["context"]
-        question = state["question"]
+    context = state["context"]
+    question = state["question"]
 
-        additional_context_template = """Here are some contexts about the question you can use if you find it helpful: {context}"""
-        additional_context = additional_context_template.format(context=context)
-        final_instruction = SYSTEM_MESSAGE + additional_context
+    additional_context_template = """Here are some contexts about the question you can use if you find it helpful: {context}"""
+    additional_context = additional_context_template.format(context=context)
+    final_instruction = SYSTEM_MESSAGE + additional_context
 
-        #answer
-        answer = llm.invoke([SystemMessage(content=final_instruction)] + [HumanMessage(content=f"Answer the question: {question}")])
+    #answer
+    answer = llm.invoke([SystemMessage(content=final_instruction)] + [HumanMessage(content=f"Answer the question: {question}")])
 
-        # Append it to state
-        return {"answer": answer}
+    # Append it to state
+    return {"answer": answer}
 
 
 builder = StateGraph(State)